Datasets:

DTU54DL
/

common-accent-proc

sentence stringlengths 11 115	accent stringclasses 15 values	input_features sequencelengths 80 80	labels sequencelengths 9 42
Men in orange vests are at work on a construction site.	India and South Asia (India, Pakistan, Sri Lanka)	[[-0.6472418308258057,-0.6472418308258057,-0.48940861225128174,0.2955693006515503,0.2943255305290222(...TRUNCATED)	[ 50258, 50259, 50359, 50363, 30505, 294, 7671, 371, 4409, 366, 412, 589, 322, 257, 6435, 3621, 13, 50257 ]
This child is getting a pedicure.	India and South Asia (India, Pakistan, Sri Lanka)	[[-0.7075793743133545,-0.7075793743133545,-0.7075793743133545,-0.16459834575653076,-0.35028553009033(...TRUNCATED)	[ 50258, 50259, 50359, 50363, 5723, 1440, 307, 1242, 257, 5670, 299, 540, 13, 50257 ]
Did you get the Mayor?	India and South Asia (India, Pakistan, Sri Lanka)	[[-0.6526447534561157,-0.6526447534561157,-0.3077355623245239,0.28790581226348877,0.0135706067085266(...TRUNCATED)	[ 50258, 50259, 50359, 50363, 17648, 291, 483, 220, 3322, 13925, 30, 50257 ]
Finally I didn't have to feel guilty for using my computer on weekends.	India and South Asia (India, Pakistan, Sri Lanka)	[[-0.926461935043335,-0.926461935043335,-0.926461935043335,-0.926461935043335,-0.926461935043335,-0.(...TRUNCATED)	[50258,50259,50359,50363,44259,286,994,380,362,220,1353,841,12341,337,1228,452,3820,322,23595,13,502(...TRUNCATED)
I'd still like to have a word with her.	India and South Asia (India, Pakistan, Sri Lanka)	[[-0.7749755382537842,-0.7749755382537842,-0.7749755382537842,-0.6209778785705566,-0.668409585952758(...TRUNCATED)	[ 50258, 50259, 50359, 50363, 40, 1116, 920, 411, 220, 1353, 362, 257, 1349, 365, 720, 13, 50257 ]
This view is wrong though.	India and South Asia (India, Pakistan, Sri Lanka)	[[-0.590583324432373,-0.590583324432373,-0.590583324432373,-0.590583324432373,-0.590583324432373,-0.(...TRUNCATED)	[ 50258, 50259, 50359, 50363, 5723, 1910, 307, 2085, 220, 3222, 13, 50257 ]
Fedric was unable to find his lucky marble.	India and South Asia (India, Pakistan, Sri Lanka)	[[-0.5188839435577393,-0.5188839435577393,-0.5188839435577393,-0.07279789447784424,-0.41854882240295(...TRUNCATED)	[ 50258, 50259, 50359, 50363, 37, 292, 1341, 390, 11299, 220, 1353, 915, 702, 6356, 26844, 13, 50257 ]
Whistle-blower Edward Snowden still lives in exile in Russia.	India and South Asia (India, Pakistan, Sri Lanka)	[[-0.5988327264785767,-0.5988327264785767,-0.5988327264785767,-0.15471220016479492,0.030863404273986(...TRUNCATED)	[50258,50259,50359,50363,2471,16088,12,5199,968,18456,14827,1556,920,2909,294,37984,294,6797,13,5025(...TRUNCATED)
I work at the hospital as a paediatrician.	India and South Asia (India, Pakistan, Sri Lanka)	[[-0.7047332525253296,-0.7047332525253296,-0.7047332525253296,-0.29167914390563965,-0.13102483749389(...TRUNCATED)	[ 50258, 50259, 50359, 50363, 40, 589, 412, 220, 3322, 4530, 382, 257, 2502, 292, 17252, 952, 13, 50257 ]
The squirrel ran up the pine tree in a spiral.	India and South Asia (India, Pakistan, Sri Lanka)	[[-0.766628623008728,-0.766628623008728,-0.766628623008728,-0.7083930969238281,-0.766628623008728,-0(...TRUNCATED)	[ 50258, 50259, 50359, 50363, 2278, 28565, 5872, 493, 220, 3322, 15113, 220, 83, 701, 294, 257, 25165, 13, 50257 ]

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YAML Metadata Warning: The task_ids "token-classification-other-acronym-identification" is not in the official list: acceptability-classification, entity-linking-classification, fact-checking, intent-classification, language-identification, multi-class-classification, multi-label-classification, multi-input-text-classification, natural-language-inference, semantic-similarity-classification, sentiment-classification, topic-classification, semantic-similarity-scoring, sentiment-scoring, sentiment-analysis, hate-speech-detection, text-scoring, named-entity-recognition, part-of-speech, parsing, lemmatization, word-sense-disambiguation, coreference-resolution, extractive-qa, open-domain-qa, closed-domain-qa, news-articles-summarization, news-articles-headline-generation, dialogue-modeling, dialogue-generation, conversational, language-modeling, text-simplification, explanation-generation, abstractive-qa, open-domain-abstractive-qa, closed-domain-qa, open-book-qa, closed-book-qa, slot-filling, masked-language-modeling, keyword-spotting, speaker-identification, audio-intent-classification, audio-emotion-recognition, audio-language-identification, multi-label-image-classification, multi-class-image-classification, face-detection, vehicle-detection, instance-segmentation, semantic-segmentation, panoptic-segmentation, image-captioning, image-inpainting, image-colorization, super-resolution, grasping, task-planning, tabular-multi-class-classification, tabular-multi-label-classification, tabular-single-column-regression, rdf-to-text, multiple-choice-qa, multiple-choice-coreference-resolution, document-retrieval, utterance-retrieval, entity-linking-retrieval, fact-checking-retrieval, univariate-time-series-forecasting, multivariate-time-series-forecasting, visual-question-answering, document-question-answering